The segmentation results are shown in Table REF . We also conduct experiments on the existing Transformer-based architecture like Swin-Transformer [1]} and Segmenter [2]}. We observe that these Transformer-based architectures are subpar on this task since they do not introduce any priors with regard to skin images to the model. Through the results, our method achieves the state-of-the-art performance in terms of Jacarrd score, pixel-AC, as well as pixel-SE, which indeed verifies the ability of the proposed method. The results of the classification task are demonstrated in Table REF . Our method achieves the best average accuracy compared with its counterparts.
